FEMA National Risk Index
Data for Eastern Shore Region
Michele Claibourn
6/24/2021
Data Source
Source: FEMA, National Risk Index, October 2020 release.
The Data Used here
The National Risk Index is intended to provide a view of the natural hazard risk within communities. While FEMA includes information on 18 natural hazards, we focus on six – coastal flooding, drought, heat wave, hurricane, riverine flooding, and strong wind – pulling measures on
- frequency (measuring the number of events or event days during a reporting period and the estimated annualized frequency or probability),
- exposure (measuring the building value, people, or agricultural value exposed to the natural hazard event), and
- historic loss ratio (measuring the proportion of building value, people, or agricultural value that has been historically impacted by the natural hazard).
The NRI uses data on natural hazards from multiple sources and estimates natural hazard frequency, exposure, and historic loss at the census tract level.
To learn more, see:
Variable descriptions
glimpse(nri)## Rows: 13
## Columns: 76
## $ OID_ <dbl> 47837, 47838, 63468, 63661, 65308, 65326, 69691, 69695, 697…
## $ NRI_ID <chr> "T51001090600", "T51001980100", "T51131930100", "T511319302…
## $ STATE <chr> "Virginia", "Virginia", "Virginia", "Virginia", "Virginia",…
## $ STATEABBRV <chr> "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA",…
## $ STATEFIPS <dbl> 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51
## $ COUNTY <chr> "Accomack", "Accomack", "Northampton", "Northampton", "Nort…
## $ COUNTYTYPE <chr> "County", "County", "County", "County", "County", "County",…
## $ COUNTYFIPS <chr> "001", "001", "131", "131", "131", "001", "001", "001", "00…
## $ STCOFIPS <dbl> 51001, 51001, 51131, 51131, 51131, 51001, 51001, 51001, 510…
## $ TRACT <chr> "090600", "980100", "930100", "930200", "930300", "090300",…
## $ TRACTFIPS <dbl> 51001090600, 51001980100, 51131930100, 51131930200, 5113193…
## $ POPULATION <dbl> 4401, 0, 4376, 3820, 4193, 2335, 2941, 5, 6234, 4907, 2849,…
## $ BUILDVALUE <dbl> 665181000, 3772000, 595521000, 380188000, 603745000, 211228…
## $ AGRIVALUE <dbl> 14720233.70, 218489.79, 21407021.39, 43535471.38, 31048507.…
## $ AREA <dbl> 49.325259, 12.157470, 53.135749, 71.502115, 87.054823, 49.5…
## $ CFLD_EVNTS <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
## $ CFLD_AFREQ <dbl> 2.743370, 2.709987, 1.202226, 1.461385, 1.292462, 2.482070,…
## $ CFLD_EXPB <dbl> 367905008, 3772000, 110856599, 86004724, 310758713, 1348494…
## $ CFLD_EXPP <dbl> 2434.14941, 0.00000, 814.59508, 864.14628, 2158.21462, 1490…
## $ CFLD_EXPPE <dbl> 18012705627, 0, 6028003599, 6394682493, 15970788179, 110310…
## $ CFLD_EXPT <dbl> 18380610635, 3772000, 6138860198, 6480687217, 16281546892, …
## $ CFLD_HLRB <dbl> 0.001493404, 0.001493404, 0.003208678, 0.003208678, 0.00320…
## $ CFLD_HLRP <dbl> 3.011133e-07, 3.011133e-07, 3.011133e-07, 3.011133e-07, 3.0…
## $ CFLD_HLRR <chr> "Very Low", "Relatively High", "Relatively Low", "Relativel…
## $ DRGT_EVNTS <dbl> 91, 42, 28, 28, 28, 63, 42, 42, 42, 35, 42, 28, 42
## $ DRGT_AFREQ <dbl> 5.055556, 2.333333, 1.555556, 1.555556, 1.555556, 3.500000,…
## $ DRGT_EXPB <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
## $ DRGT_EXPP <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
## $ DRGT_EXPPE <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
## $ DRGT_EXPA <dbl> 4848309, 0, 0, 43535471, 23747093, 0, 0, 0, 39002636, 30104…
## $ DRGT_EXPT <dbl> 4848309, 0, 0, 43535471, 23747093, 0, 0, 0, 39002636, 30104…
## $ DRGT_HLRB <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
## $ DRGT_HLRP <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
## $ DRGT_HLRA <dbl> 0.001584889, 0.001584889, 0.003693487, 0.003693487, 0.00369…
## $ DRGT_HLRR <chr> "Relatively Moderate", "No Rating", "No Rating", "Very High…
## $ HWAV_EVNTS <dbl> 6, 11, 7, 7, 7, 6, 6, 6, 6, 6, 6, 6, 11
## $ HWAV_AFREQ <dbl> 0.4942339, 0.5766009, 0.5766063, 0.5766063, 0.5766063, 0.49…
## $ HWAV_EXPB <dbl> 665180718, 3772000, 595520944, 380187676, 603744461, 211227…
## $ HWAV_EXPP <dbl> 4400.999, 0.000, 4375.999, 3819.996, 4192.997, 2334.998, 29…
## $ HWAV_EXPPE <dbl> 32567391524, 0, 32382392576, 28267973910, 31028174325, 1727…
## $ HWAV_EXPT <dbl> 33232572241, 3772000, 32977913520, 28648161585, 31631918786…
## $ HWAV_HLRB <dbl> 3.60888e-10, 3.60888e-10, 2.97900e-12, 2.97900e-12, 2.97900…
## $ HWAV_HLRP <dbl> 2.901945e-07, 2.901945e-07, 2.901945e-07, 2.901945e-07, 2.9…
## $ HWAV_HLRR <chr> "Very Low", "Very Low", "Very Low", "Very Low", "Very Low",…
## $ HRCN_EVNTS <dbl> 33, 21, 28, 22, 25, 26, 21, 21, 26, 24, 25, 26, 27
## $ HRCN_AFREQ <dbl> 0.1967287, 0.2214110, 0.2239624, 0.2238779, 0.2406999, 0.22…
## $ HRCN_EXPB <dbl> 664767958, 3769524, 595340857, 380080256, 603484965, 211227…
## $ HRCN_EXPP <dbl> 4398.720, 0.000, 4374.935, 3818.995, 4191.471, 2334.992, 29…
## $ HRCN_EXPPE <dbl> 32550526424, 0, 32374516646, 28260566446, 31016886195, 1727…
## $ HRCN_EXPT <dbl> 33215294382, 3769524, 32969857503, 28640646702, 31620371160…
## $ HRCN_HLRB <dbl> 0.0006539852, 0.0006539852, 0.0011742747, 0.0011742747, 0.0…
## $ HRCN_HLRP <dbl> 6.528385e-07, 6.528385e-07, 1.377019e-06, 1.377019e-06, 1.3…
## $ HRCN_HLRR <chr> "Very Low", "Relatively Moderate", "Very Low", "Very Low", …
## $ RFLD_EVNTS <dbl> 13, 13, 6, 6, 6, 13, 13, 13, 13, 13, 13, 13, 13
## $ RFLD_AFREQ <dbl> 0.5909091, 0.5909091, 0.2727273, 0.2727273, 0.2727273, 0.59…
## $ RFLD_EXPB <dbl> 202317003.4, 3429843.9, 46695447.8, 44570613.2, 149882632.4…
## $ RFLD_EXPP <dbl> 1408.94892, 0.00000, 276.46151, 329.02285, 763.49921, 919.0…
## $ RFLD_EXPPE <dbl> 10426222026, 0, 2045815190, 2434769122, 5649894147, 6800847…
## $ RFLD_EXPA <dbl> 3092313.16, 175094.85, 1135609.61, 2408639.57, 1343780.69, …
## $ RFLD_EXPT <dbl> 1.063163e+10, 3.604939e+06, 2.093646e+09, 2.481748e+09, 5.8…
## $ RFLD_HLRB <dbl> 0.0004153736, 0.0004153736, 0.0037380237, 0.0037380237, 0.0…
## $ RFLD_HLRP <dbl> 3.925184e-06, 3.925184e-06, 1.824847e-05, 1.824847e-05, 1.8…
## $ RFLD_HLRA <dbl> 0.001257540, 0.001257540, 0.008719085, 0.008719085, 0.00871…
## $ RFLD_HLRR <chr> "Very Low", "Very Low", "Very Low", "Very Low", "Very Low",…
## $ SWND_EVNTS <dbl> 209, 161, 150, 146, 115, 162, 162, 162, 151, 155, 158, 142,…
## $ SWND_AFREQ <dbl> 6.533043, 5.062500, 4.710873, 4.582564, 3.599022, 5.076151,…
## $ SWND_EXPB <dbl> 665181000, 3772000, 595521000, 380188000, 603745000, 211228…
## $ SWND_EXPP <dbl> 4401, 0, 4376, 3820, 4193, 2335, 2941, 5, 6234, 4907, 2849,…
## $ SWND_EXPPE <dbl> 32567400000, 0, 32382400000, 28268000000, 31028200000, 1727…
## $ SWND_EXPA <dbl> 14720233.70, 218489.79, 21407021.39, 43535471.38, 31048507.…
## $ SWND_EXPT <dbl> 33247301234, 3990490, 32999328021, 28691723471, 31662993507…
## $ SWND_HLRB <dbl> 1.648158e-05, 1.648158e-05, 1.927672e-05, 1.927672e-05, 1.9…
## $ SWND_HLRP <dbl> 6.850051e-08, 6.850051e-08, 3.424598e-07, 3.424598e-07, 3.4…
## $ SWND_HLRA <dbl> 2.435583e-06, 2.435583e-06, 2.435583e-06, 2.435583e-06, 2.4…
## $ SWND_HLRR <chr> "Very Low", "Very Low", "Very Low", "Very Low", "Very Low",…
## $ NRI_VER <chr> "October 2020", "October 2020", "October 2020", "October 20…Observations are census tract estimates of…
- Population, building value, agricultural value, and area within tract
- Natural hazards include: CFLD - coastal flooding, DRGT - drought, HWAV - heat wave, HRCN - hurricane, RFLD - riverine flooding, SWND - strong wind
- Hazard measures include: EVNTS - number of events in recording period, AFREQ - annualized frequency (# events/# years in recording period)
- Exposure measures include: EXPB - building value exposure, EXPP - population exposure, EXPE - population equivalence exposure, EXPA - agricultural value exposure
- Historic loss ratio measures include: HLRB - historic loss ratio for building value, HLRA - historicla loss ratio for agriculture, HLRP - historical loss ratio for population, HLRR - historic loss ratio overall
Summaries
5-number summaries of (non-missing) numeric variables (remove tract identifiers)
nri %>% select(-c(OID_:STATEFIPS, COUNTYTYPE:TRACTFIPS, NRI_VER)) %>%
select(where(~is.numeric(.x) && !is.na(.x))) %>%
as.data.frame() %>%
stargazer(., type = "text", title = "Summary Statistics", digits = 0,
summary.stat = c("mean", "sd", "min", "median", "max"))##
## Summary Statistics
## ================================================================================
## Statistic Mean St. Dev. Min Median Max
## --------------------------------------------------------------------------------
## POPULATION 3,504 1,942 0 3,820 6,234
## BUILDVALUE 445,064,231 263,814,332 3,772,000 547,772,000 813,756,000
## AGRIVALUE 19,943,077 15,182,275 31,301 21,407,021 43,535,471
## AREA 51 27 7 53 87
## CFLD_AFREQ 2 1 1 2 3
## CFLD_EXPB 199,509,533 198,615,187 3,772,000 134,849,422 736,404,000
## CFLD_EXPP 1,402 936 0 1,452 2,941
## CFLD_EXPPE 10,371,633,091 6,922,727,785 0 10,746,133,053 21,763,400,000
## CFLD_EXPT 10,571,142,624 7,099,434,508 3,772,000 10,926,364,382 22,499,804,000
## CFLD_HLRB 0 0 0 0 0
## CFLD_HLRP 0 0 0 0 0
## DRGT_EVNTS 43 17 28 42 91
## DRGT_AFREQ 2 1 2 2 5
## DRGT_EXPA 12,767,239 16,840,163 0 0 43,535,471
## DRGT_EXPT 12,767,239 16,840,163 0 0 43,535,471
## DRGT_HLRA 0 0 0 0 0
## HWAV_EVNTS 7 2 6 6 11
## HWAV_AFREQ 1 0 0 0 1
## HWAV_EXPB 445,064,081 263,814,292 3,772,000 547,771,848 813,755,973
## HWAV_EXPP 3,504 1,942 0 3,820 6,234
## HWAV_EXPPE 25,930,157,957 14,370,703,000 0 28,267,973,910 46,131,584,530
## HWAV_EXPT 26,375,222,038 14,594,282,423 3,772,000 28,648,161,585 46,679,356,378
## HWAV_HLRB 0 0 0 0 0
## HWAV_HLRP 0 0 0 0 0
## HRCN_EVNTS 25 3 21 25 33
## HRCN_AFREQ 0 0 0 0 0
## HRCN_EXPB 444,801,528 263,624,465 3,769,524 547,726,825 813,598,176
## HRCN_EXPP 3,503 1,942 0 3,819 6,234
## HRCN_EXPPE 25,920,530,241 14,369,165,198 0 28,260,566,446 46,129,744,254
## HRCN_EXPT 26,365,331,769 14,592,649,165 3,769,524 28,640,646,702 46,677,471,079
## HRCN_HLRB 0 0 0 0 0
## HRCN_HLRP 0 0 0 0 0
## RFLD_EVNTS 11 3 6 13 13
## RFLD_AFREQ 1 0 0 1 1
## RFLD_EXPB 106,469,319 161,601,174 301,320 51,513,125 608,324,065
## RFLD_EXPP 605 662 0 340 2,374
## RFLD_EXPPE 4,479,443,695 4,897,974,424 0 2,517,678,037 17,566,176,693
## RFLD_EXPA 1,935,370 1,612,333 26,074 1,964,586 5,149,665
## RFLD_EXPT 4,587,848,385 5,052,492,472 364,660 2,574,672,609 18,174,526,832
## RFLD_HLRB 0 0 0 0 0
## RFLD_HLRP 0 0 0 0 0
## RFLD_HLRA 0 0 0 0 0
## SWND_EVNTS 156 20 115 158 209
## SWND_AFREQ 5 1 4 5 7
## SWND_EXPB 445,064,231 263,814,332 3,772,000 547,772,000 813,756,000
## SWND_EXPP 3,504 1,942 0 3,820 6,234
## SWND_EXPPE 25,930,169,231 14,370,706,471 0 28,268,000,000 46,131,600,000
## SWND_EXPA 19,943,077 15,182,275 31,301 21,407,021 43,535,471
## SWND_EXPT 26,395,176,538 14,606,328,047 3,990,490 28,691,723,471 46,718,374,636
## SWND_HLRB 0 0 0 0 0
## SWND_HLRP 0 0 0 0 0
## SWND_HLRA 0 0 0 0 0
## --------------------------------------------------------------------------------Summaries of (non-missing) character variables (remove tract identifiers)
nri %>% select(-c(OID_:STATEFIPS, COUNTYTYPE:TRACTFIPS, NRI_VER)) %>%
select(where (~is.character(.x))) %>% map(tabyl)## $COUNTY
## .x[[i]] n percent
## Accomack 10 0.7692308
## Northampton 3 0.2307692
##
## $CFLD_HLRR
## .x[[i]] n percent
## Relatively High 1 0.07692308
## Relatively Low 4 0.30769231
## Relatively Moderate 1 0.07692308
## Very Low 7 0.53846154
##
## $DRGT_HLRR
## .x[[i]] n percent
## No Rating 7 0.5384615
## Relatively Moderate 4 0.3076923
## Very High 2 0.1538462
##
## $HWAV_HLRR
## .x[[i]] n percent
## Very Low 13 1
##
## $HRCN_HLRR
## .x[[i]] n percent
## Relatively Low 1 0.07692308
## Relatively Moderate 1 0.07692308
## Very Low 11 0.84615385
##
## $RFLD_HLRR
## .x[[i]] n percent
## Very Low 13 1
##
## $SWND_HLRR
## .x[[i]] n percent
## Very Low 13 1Visual distribution
Frequency distribution across tracts:
Tract assets
nri %>% select(TRACTFIPS:AREA) %>%
pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>%
ggplot(aes(x = value, fill = measure)) +
scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
geom_histogram() +
facet_wrap(~measure, scales = "free")
Tract hazards: Coastal Flooding
# Tract hazards: CFLD
nri %>% select(contains("CFLD"), TRACTFIPS) %>% select(-contains("HLRR")) %>%
pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>%
ggplot(aes(x = value, fill = measure)) +
geom_histogram() +
scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
facet_wrap(~measure, scales = "free")
Tract hazards: Drought
nri %>% select(contains("DRGT"), TRACTFIPS) %>% select(-contains("HLRR")) %>%
pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>%
ggplot(aes(x = value, fill = measure)) +
geom_histogram() +
scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
facet_wrap(~measure, scales = "free")
Tract hazards: Heat Wave
nri %>% select(contains("HWAV"), TRACTFIPS) %>% select(-contains("HLRR")) %>%
pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>%
ggplot(aes(x = value, fill = measure)) +
geom_histogram() +
scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
facet_wrap(~measure, scales = "free")
Tract hazards: Hurricane
nri %>% select(contains("HRCN"), TRACTFIPS) %>% select(-contains("HLRR")) %>%
pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>%
ggplot(aes(x = value, fill = measure)) +
geom_histogram() +
scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
facet_wrap(~measure, scales = "free")
Tract hazards: Riverine Flooding
nri %>% select(contains("RFLD"), TRACTFIPS) %>% select(-contains("HLRR")) %>%
pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>%
ggplot(aes(x = value, fill = measure)) +
geom_histogram() +
scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
facet_wrap(~measure, scales = "free")
Tract hazards: Strong Wind
nri %>% select(contains("SWND"), TRACTFIPS) %>% select(-contains("HLRR")) %>%
pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>%
ggplot(aes(x = value, fill = measure)) +
geom_histogram() +
scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
facet_wrap(~measure, scales = "free")
Maps
Variation across tracts
Coastal Flooding
# CFLD
pal <- colorNumeric("plasma", reverse = TRUE, domain = eastern_nri$CFLD_AFREQ) # viridis
leaflet() %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(data = eastern_nri,
fillColor = ~pal(CFLD_AFREQ),
weight = 1,
opacity = 1,
color = "white",
fillOpacity = 0.6,
highlight = highlightOptions(
weight = 2,
fillOpacity = 0.8,
bringToFront = T
),
popup = paste0("Tract Number: ", eastern_nri$NAME, "<br>",
"Ann. Freq.: ", round(eastern_nri$CFLD_AFREQ, 2))
) %>%
addLegend("bottomright", pal = pal, values = eastern_nri$CFLD_AFREQ,
title = "Coastal Flooding-#/year", opacity = 0.7)Droughts
# DRGT
pal <- colorNumeric("plasma", reverse = TRUE, domain = eastern_nri$DRGT_AFREQ) # viridis
leaflet() %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(data = eastern_nri,
fillColor = ~pal(DRGT_AFREQ),
weight = 1,
opacity = 1,
color = "white",
fillOpacity = 0.6,
highlight = highlightOptions(
weight = 2,
fillOpacity = 0.8,
bringToFront = T
),
popup = paste0("Tract Number: ", eastern_nri$NAME, "<br>",
"Ann. Freq.: ", round(eastern_nri$DRGT_AFREQ, 2))
) %>%
addLegend("bottomright", pal = pal, values = eastern_nri$DRGT_AFREQ,
title = "Drought-#/year", opacity = 0.7)Heat Wave
# HWAV
pal <- colorNumeric("plasma", reverse = TRUE, domain = eastern_nri$HWAV_AFREQ) # viridis
leaflet() %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(data = eastern_nri,
fillColor = ~pal(HWAV_AFREQ),
weight = 1,
opacity = 1,
color = "white",
fillOpacity = 0.6,
highlight = highlightOptions(
weight = 2,
fillOpacity = 0.8,
bringToFront = T
),
popup = paste0("Tract Number: ", eastern_nri$NAME, "<br>",
"Ann. Freq.: ", round(eastern_nri$HWAV_AFREQ, 2))
) %>%
addLegend("bottomright", pal = pal, values = eastern_nri$HWAV_AFREQ,
title = "Heat Wave-#/year", opacity = 0.7)Hurricane
# HRCN
pal <- colorNumeric("plasma", reverse = TRUE, domain = eastern_nri$HRCN_AFREQ) # viridis
leaflet() %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(data = eastern_nri,
fillColor = ~pal(HRCN_AFREQ),
weight = 1,
opacity = 1,
color = "white",
fillOpacity = 0.6,
highlight = highlightOptions(
weight = 2,
fillOpacity = 0.8,
bringToFront = T
),
popup = paste0("Tract Number: ", eastern_nri$NAME, "<br>",
"Ann. Freq.: ", round(eastern_nri$HRCN_AFREQ, 2))
) %>%
addLegend("bottomright", pal = pal, values = eastern_nri$HRCN_AFREQ,
title = "Hurricane-#/year", opacity = 0.7)Riverine Flooding
# RFLD
pal <- colorNumeric("plasma", reverse = TRUE, domain = eastern_nri$RFLD_AFREQ) # viridis
leaflet() %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(data = eastern_nri,
fillColor = ~pal(RFLD_AFREQ),
weight = 1,
opacity = 1,
color = "white",
fillOpacity = 0.6,
highlight = highlightOptions(
weight = 2,
fillOpacity = 0.8,
bringToFront = T
),
popup = paste0("Tract Number: ", eastern_nri$NAME, "<br>",
"Ann. Freq.: ", round(eastern_nri$RFLD_AFREQ, 2))
) %>%
addLegend("bottomright", pal = pal, values = eastern_nri$RFLD_AFREQ,
title = "Riverine Flooding-#/year", opacity = 0.7)Strong Wind
# SWND
pal <- colorNumeric("plasma", reverse = TRUE, domain = eastern_nri$SWND_AFREQ) # viridis
leaflet() %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(data = eastern_nri,
fillColor = ~pal(SWND_AFREQ),
weight = 1,
opacity = 1,
color = "white",
fillOpacity = 0.6,
highlight = highlightOptions(
weight = 2,
fillOpacity = 0.8,
bringToFront = T
),
popup = paste0("Tract Number: ", eastern_nri$NAME, "<br>",
"Ann. Freq.: ", round(eastern_nri$SWND_AFREQ, 2))
) %>%
addLegend("bottomright", pal = pal, values = eastern_nri$SWND_AFREQ,
title = "Strong Wind-#/year", opacity = 0.7)Nota Bene
- Several hazard rates are dominated by regional measures, with little variation identified within the region.